Practical guidelines for B-cell receptor repertoire sequencing analysis

Heavy chain sequence-based classifier for the specificity of human antibodies

Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnostics. High-throughput sequencing technologies have promoted comprehensive profiling of the immune repertoire, which has resulted in large amounts of antibody sequences that remain to be further analyzed. In this study, antibodies were downloaded from IMGT/LIGM-DB and Sequence Read Archive databases. Contributing features from antibody heavy chains were formulated as numerical inputs and fed into an ensemble machine learning classifier to classify the antigen specificity of six classes of antibodies, namely anti-HIV-1, anti-influenza virus, anti-pneumococcal polysaccharide, anti-citrullinated protein, anti-tetanus toxoid and anti-hepatitis B virus. The classifier was validated using cross-validation and a testing dataset. The ensemble classifier achieved a macro-average area under the receiver operating characteristic curve (AUC) of 0.9246 from the 10-fold cross-validation, and 0.9264 for the testing dataset. Among the contributing features, the contribution of the complementarity-determining regions was 53.1% and that of framework regions was 46.9%, and the amino acid mutation rates occupied the first and second ranks among the top five contributing features. The classifier and insights provided in this study could promote the mechanistic study, isolation and utilization of potential therapeutic antibodies.

Computational Inference, Validation, and Analysis of 5'UTR-Leader Sequences of Alleles of Immunoglobulin Heavy Chain Variable Genes

Upstream and downstream sequences of immunoglobulin genes may affect the expression of such genes. However, these sequences are rarely studied or characterized in most studies of immunoglobulin repertoires. Inference from large, rearranged immunoglobulin transcriptome data sets offers an opportunity to define the upstream regions (5'-untranslated regions and leader sequences). We have now established a new data pre-processing procedure to eliminate artifacts caused by a 5'-RACE library generation process, reanalyzed a previously studied data set defining human immunoglobulin heavy chain genes, and identified novel upstream regions, as well as previously identified upstream regions that may have been identified in error. Upstream sequences were also identified for a set of previously uncharacterized germline gene alleles. Several novel upstream region variants were validated, for instance by their segregation to a single haplotype in heterozygotic subjects. SNPs representing several sequence variants were identified from population data. Finally, based on the outcomes of the analysis, we define a set of testable hypotheses with respect to the placement of particular alleles in complex IGHV locus haplotypes, and discuss the evolutionary relatedness of particular heavy chain variable genes based on sequences of their upstream regions.

Isolation of monoclonal antibodies from anti-synthetase syndrome patients and affinity maturation by recombination of independent somatic variants

The autoimmune disease known as Jo-1 positive anti-synthetase syndrome (ASS) is characterized by circulating antibody titers to histidyl-tRNA synthetase (HARS), which may play a role in modulating the non-canonical functions of HARS. Monoclonal antibodies to HARS were isolated by single-cell screening and sequencing from three Jo-1 positive ASS patients and shown to be of high affinity, covering diverse epitope space. The immune response was further characterized by repertoire sequencing from the most productive of the donor samples. In line with previous studies of autoimmune repertoires, these antibodies tended to have long complementarity-determining region H3 sequences with more positive-charged residues than average. Clones of interest were clustered into groups with related sequences, allowing us to observe different somatic mutations in related clones. We postulated that these had found alternate structural solutions for high affinity binding, but that mutations might be transferable between clones to further enhance binding affinity. Transfer of somatic mutations between antibodies within the same clonal group was able to enhance binding affinity in a number of cases, including beneficial transfer of a mutation from a lower affinity clone into one of higher affinity. Affinity enhancement was seen with mutation transfer both between related single-cell clones, and directly from related repertoire sequences. To our knowledge, this is the first demonstration of somatic hypermutation transfer from repertoire sequences to further mature in vivo derived antibodies, and represents an additional tool to aid in affinity maturation for the development of antibodies.

Progress and challenges in mass spectrometry-based analysis of antibody repertoires

Humoral immunity is divided into the cellular B cell and protein-level antibody responses. High-throughput sequencing has advanced our understanding of both these fundamental aspects of B cell immunology as well as aspects pertaining to vaccine and therapeutics biotechnology. Although the protein-level serum and mucosal antibody repertoire make major contributions to humoral protection, the sequence composition and dynamics of antibody repertoires remain underexplored. This limits insight into important immunological and biotechnological parameters such as the number of antigen-specific antibodies, which are for example, relevant for pathogen neutralization, microbiota regulation, severity of autoimmunity, and therapeutic efficacy. High-resolution mass spectrometry (MS) has allowed initial insights into the antibody repertoire. We outline current challenges in MS-based sequence analysis of antibody repertoires and propose strategies for their resolution.

CRIS: complete reconstruction of immunoglobulin V-D-J sequences from RNA-seq data

MOTIVATION

B cells display remarkable diversity in producing B-cell receptors through recombination of immunoglobulin (Ig) V-D-J genes. Somatic hypermutation (SHM) of immunoglobulin heavy chain variable (IGHV) genes are used as a prognostic marker in B-cell malignancies. Clinically, IGHV mutation status is determined by targeted Sanger sequencing which is a resource-intensive and low-throughput procedure. Here, we describe a bioinformatic pipeline, CRIS (Complete Reconstruction of Immunoglobulin IGHV-D-J Sequences) that uses RNA sequencing (RNA-seq) datasets to reconstruct IGHV-D-J sequences and determine IGHV SHM status.

RESULTS

CRIS extracts RNA-seq reads aligned to Ig gene loci, performs assembly of Ig transcripts and aligns the resulting contigs to reference Ig sequences to enumerate and classify SHMs in the IGHV gene sequence. CRIS improves on existing tools that infer the B-cell receptor repertoire from RNA-seq data using a portion IGHV gene segment by de novo assembly. We show that the SHM status identified by CRIS using the entire IGHV gene segment is highly concordant with clinical classification in three independent chronic lymphocytic leukemia patient cohorts.

AVAILABILITY AND IMPLEMENTATION

The CRIS pipeline is available under the MIT License from https://github.com/Rashedul/CRIS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics Advances online.

The signs of negative selection in IGHV framework regions are associated with worse overall survival of chronic lymphocytic leukemia patients

The mutational status of the variable region of the immunoglobulin heavy chain (IGHV) genes remains the most significant prognostic factor in chronic lymphocytic leukemia (CLL) patients. However, the groups of mutated (M) and unmutated (UM) patients are also heterogeneous, and additional markers are used for a more accurate prognosis. The aim of our work was to determine the prognostic value of the signs of antigen selection determined by BASELINe statistics in M IGHV sequences of CLL patients. Clinical data, IGHV gene configuration, TP53, NOTCH1, SF3B1 mutations were analyzed in 127 CLL patients with M IGHV sequences. The median OS of patients with negative selection in the framework regions (FWRs) of IGHV genes was 120 months compared to 202 month in other CLL patients (P = 0.016). In multivariate Cox regression analysis Binet stage C vs A + B (P < 0.0001), SF3B1 mutations (P < 0.0001), negative selection in the FWRs (HR P = 0.007), and age ≥65 years (P = 0.034) were powerful adverse prognostic factors for OS in CLL patients with M IGHV genes. These preliminary data suggest that the signs of antigen-driven selection may be used as a prognostic factor in CLL patients with M IGHV genes in combination with other markers.

Access to ultra-long IgG CDRH3 bovine antibody sequences using short read sequencing technology

The advances in high-throughput DNA sequencing and recombinant antibody technologies has presented new methods for characterizing antibody repertoires and significantly increased our understanding on the functional role of antibodies in immunity and their use in diagnostics, vaccine antigen design and as biological therapeutics. A subset of Bos taurus antibodies possesses unique ultra-long third complementary-determining region of the heavy chain (CDRH3) and are of special interest because they are thought to have unique functional abilities of broadly neutralizing properties - a functional role that has not been fully explored in vaccine development. Next generation sequencing technologies that are widely used to profile immunoglobulin (Ig) repertoires are based on short-read methods such as the Illumina technology. Although this technology has worked well in sequencing Ig V-D-J regions of most jawed vertebrates, it has faced serious technical challenges with sequencing regions in bovine Ig bearing ultra-long CDRH3 sequences, which are longer than 120 bp. To overcome this limitation, we have developed a sequencing strategy based on nested PCR products that allows sequence assembly of full-length bovine Ig heavy-chain (IgH) V-D-J regions. We have used this strategy to sequence IgH V-D-J regions of two Bos indicus breeds, Ankole and Boran. We confirm the presence of ultra-long CDRH3 sequences in IgG transcripts in both African cattle breeds, and provide preliminary evidence for differences and preferences in germline V_H, D_H and J_H allele gene usage as well as differences in the length of the VH region in the two bovine breeds. Our method provides tools that should allow more robust analyses of ultra-long CDRH3 sequences aiding antibody and epitope discovery in different cattle breeds and their role in mediating immunity.

Quantitative characterization of the B cell receptor repertoires of human immunized with commercial rabies virus vaccine

Humoral immunity is crucial for an efficient host immune response against rabies virus (RABV) infection. But the B cell receptor (BCR) repertoire in human after RABV vaccine immunization remained unclear. To study the BCR repertoires in peripheral blood mononuclear cells (PBMCs) of human immunized with rabies virus vaccine. In this study, we conducted BCR complementarity determining region 3 (CDR3) repertoires in 4 healthy volunteers before and after immunization with RABV vaccine by high-throughput sequencing. The bioinformatics analysis process was performed. The results showed that RABV vaccination changed the BCR diversity and the usage of V/J gene segments, as well as V-J pairing. B cell clone expansion was induced by the vaccination and sequences of high expand CDR3 aa clones were identified. To the best of our knowledge, we firstly quantitative characterized B cell receptor repertoire of human immunized with c rabies virus vaccine. It might provide us with new insights into B cell receptor condition after RABV vaccination.

Immune2vec: Embedding B/T Cell Receptor Sequences in ℝ N Using Natural Language Processing

The adaptive branch of the immune system learns pathogenic patterns and remembers them for future encounters. It does so through dynamic and diverse repertoires of T- and B- cell receptors (TCR and BCRs, respectively). These huge immune repertoires in each individual present investigators with the challenge of extracting meaningful biological information from multi-dimensional data. The ability to embed these DNA and amino acid textual sequences in a vector-space is an important step towards developing effective analysis methods. Here we present Immune2vec, an adaptation of a natural language processing (NLP)-based embedding technique for BCR repertoire sequencing data. We validate Immune2vec on amino acid 3-gram sequences, continuing to longer BCR sequences, and finally to entire repertoires. Our work demonstrates Immune2vec to be a reliable low-dimensional representation that preserves relevant information of immune sequencing data, such as n-gram properties and IGHV gene family classification. Applying Immune2vec along with machine learning approaches to patient data exemplifies how distinct clinical conditions can be effectively stratified, indicating that the embedding space can be used for feature extraction and exploratory data analysis.

Platypus: an open-access software for integrating lymphocyte single-cell immune repertoires with transcriptomes

High-throughput single-cell sequencing (scSeq) technologies are revolutionizing the ability to molecularly profile B and T lymphocytes by offering the opportunity to simultaneously obtain information on adaptive immune receptor repertoires (VDJ repertoires) and transcriptomes. An integrated quantification of immune repertoire parameters, such as germline gene usage, clonal expansion, somatic hypermutation and transcriptional states opens up new possibilities for the high-resolution analysis of lymphocytes and the inference of antigen-specificity. While multiple tools now exist to investigate gene expression profiles from scSeq of transcriptomes, there is a lack of software dedicated to single-cell immune repertoires. Here, we present Platypus, an open-source software platform providing a user-friendly interface to investigate B-cell receptor and T-cell receptor repertoires from scSeq experiments. Platypus provides a framework to automate and ease the analysis of single-cell immune repertoires while also incorporating transcriptional information involving unsupervised clustering, gene expression and gene ontology. To showcase the capabilities of Platypus, we use it to analyze and visualize single-cell immune repertoires and transcriptomes from B and T cells from convalescent COVID-19 patients, revealing unique insight into the repertoire features and transcriptional profiles of clonally expanded lymphocytes. Platypus will expedite progress by facilitating the analysis of single-cell immune repertoire and transcriptome sequencing.

Machine Learning Analysis of Naïve B-Cell Receptor Repertoires Stratifies Celiac Disease Patients and Controls

Celiac disease (CeD) is a common autoimmune disorder caused by an abnormal immune response to dietary gluten proteins. The disease has high heritability. HLA is the major susceptibility factor, and the HLA effect is mediated via presentation of deamidated gluten peptides by disease-associated HLA-DQ variants to CD4+ T cells. In addition to gluten-specific CD4+ T cells the patients have antibodies to transglutaminase 2 (autoantigen) and deamidated gluten peptides. These disease-specific antibodies recognize defined epitopes and they display common usage of specific heavy and light chains across patients. Interactions between T cells and B cells are likely central in the pathogenesis, but how the repertoires of naïve T and B cells relate to the pathogenic effector cells is unexplored. To this end, we applied machine learning classification models to naïve B cell receptor (BCR) repertoires from CeD patients and healthy controls. Strikingly, we obtained a promising classification performance with an F1 score of 85%. Clusters of heavy and light chain sequences were inferred and used as features for the model, and signatures associated with the disease were then characterized. These signatures included amino acid (AA) 3-mers with distinct bio-physiochemical characteristics and enriched V and J genes. We found that CeD-associated clusters can be identified and that common motifs can be characterized from naïve BCR repertoires. The results may indicate a genetic influence by BCR encoding genes in CeD. Analysis of naïve BCRs as presented here may become an important part of assessing the risk of individuals to develop CeD. Our model demonstrates the potential of using BCR repertoires and in particular, naïve BCR repertoires, as disease susceptibility markers.

Alignment free identification of clones in B cell receptor repertoires

Following antigenic challenge, activated B cells rapidly expand and undergo somatic hypermutation, yielding groups of clonally related B cells with diversified immunoglobulin receptors. Inference of clonal relationships based on the receptor sequence is an essential step in many adaptive immune receptor repertoire sequencing studies. These relationships are typically identified by a multi-step process that involves: (i) grouping sequences based on shared V and J gene assignments, and junction lengths and (ii) clustering these sequences using a junction-based distance. However, this approach is sensitive to the initial gene assignments, which are error-prone, and fails to identify clonal relatives whose junction length has changed through accumulation of indels. Through defining a translation-invariant feature space in which we cluster the sequences, we develop an alignment free clonal identification method that does not require gene assignments and is not restricted to a fixed junction length. This alignment free approach has higher sensitivity compared to a typical junction-based distance method without loss of specificity and PPV. While the alignment free procedure identifies clones that are broadly consistent with the junction-based distance method, it also identifies clones with characteristics (multiple V or J gene assignments or junction lengths) that are not detectable with the junction-based distance method.

Public Baseline and shared response structures support the theory of antibody repertoire functional commonality

The naïve antibody/B-cell receptor (BCR) repertoires of different individuals ought to exhibit significant functional commonality, given that most pathogens trigger an effective antibody response to immunodominant epitopes. Sequence-based repertoire analysis has so far offered little evidence for this phenomenon. For example, a recent study estimated the number of shared ('public') antibody clonotypes in circulating baseline repertoires to be around 0.02% across ten unrelated individuals. However, to engage the same epitope, antibodies only require a similar binding site structure and the presence of key paratope interactions, which can occur even when their sequences are dissimilar. Here, we search for evidence of geometric similarity/convergence across human antibody repertoires. We first structurally profile naïve ('baseline') antibody diversity using snapshots from 41 unrelated individuals, predicting all modellable distinct structures within each repertoire. This analysis uncovers a high (much greater than random) degree of structural commonality. For instance, around 3% of distinct structures are common to the ten most diverse individual samples ('Public Baseline' structures). Our approach is the first computational method to find levels of BCR commonality commensurate with epitope immunodominance and could therefore be harnessed to find more genetically distant antibodies with same-epitope complementarity. We then apply the same structural profiling approach to repertoire snapshots from three individuals before and after flu vaccination, detecting a convergent structural drift indicative of recognising similar epitopes ('Public Response' structures). We show that Antibody Model Libraries derived from Public Baseline and Public Response structures represent a powerful geometric basis set of low-immunogenicity candidates exploitable for general or target-focused therapeutic antibody screening.

Longevity, clonal relationship, and transcriptional program of celiac disease-specific plasma cells

Disease-specific plasma cells (PCs) reactive with transglutaminase 2 (TG2) or deamidated gluten peptides (DGPs) are abundant in celiac disease (CeD) gut lesions. Their contribution toward CeD pathogenesis is unclear. We assessed expression of markers associated with PC longevity in 15 untreated and 26 treated CeD patients in addition to 13 non-CeD controls and performed RNA sequencing with clonal inference and transcriptomic analysis of 3,251 single PCs. We observed antigen-dependent V-gene selection and stereotypic antibodies. Generation of recombinant DGP-specific antibodies revealed a key role of a heavy chain residue that displays polymorphism, suggesting that immunoglobulin gene polymorphisms may influence CeD-specific antibody responses. We identified transcriptional differences between CeD-specific and non-disease-specific PCs and between short-lived and long-lived PCs. The short-lived CD19+CD45+ phenotype dominated in untreated and short-term-treated CeD, in particular among disease-specific PCs but also in the general PC population. Thus, the disease lesion of untreated CeD is characterized by massive accumulation of short-lived PCs that are not only directed against disease-specific antigens.

Breast cancer is marked by specific, Public T-cell receptor CDR3 regions shared by mice and humans

The partial success of tumor immunotherapy induced by checkpoint blockade, which is not antigen-specific, suggests that the immune system of some patients contain antigen receptors able to specifically identify tumor cells. Here we focused on T-cell receptor (TCR) repertoires associated with spontaneous breast cancer. We studied the alpha and beta chain CDR3 domains of TCR repertoires of CD4 T cells using deep sequencing of cell populations in mice and applied the results to published TCR sequence data obtained from human patients. We screened peripheral blood T cells obtained monthly from individual mice spontaneously developing breast tumors by 5 months. We then looked at identical TCR sequences in published human studies; we used TCGA data from tumors and healthy tissues of 1,256 breast cancer resections and from 4 focused studies including sequences from tumors, lymph nodes, blood and healthy tissues, and from single cell dataset of 3 breast cancer subjects. We now report that mice spontaneously developing breast cancer manifest shared, Public CDR3 regions in both their alpha and beta and that a significant number of women with early breast cancer manifest identical CDR3 sequences. These findings suggest that the development of breast cancer is associated, across species, with biomarker, exclusive TCR repertoires.

Cytologic and Molecular Diagnostics for Vitreoretinal Lymphoma: Current Approaches and Emerging Single-Cell Analyses

Vitreoretinal lymphoma (VRL) is a rare ocular malignancy that manifests as diffuse large B-cell lymphoma. Early and accurate diagnosis is essential to prevent mistreatment and to reduce the high morbidity and mortality associated with VRL. The disease can be diagnosed using various methods, including cytology, immunohistochemistry, cytokine analysis, flow cytometry, and molecular analysis of bulk vitreous aspirates. Despite these options, VRL diagnosis remains challenging, as samples are often confounded by low cellularity, the presence of debris and non-target immunoreactive cells, and poor cytological preservation. As such, VRL diagnostic accuracy is limited by both false-positive and false-negative outcomes. Missed or inappropriate diagnosis may cause delays in treatment, which can have life-threatening consequences for patients with VRL. In this review, we summarize current knowledge and the diagnostic modalities used for VRL diagnosis. We also highlight several emerging molecular techniques, including high-resolution single cell-based analyses, which may enable more comprehensive and precise VRL diagnoses.

A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-pertussis toxoid antibodies

Due to their shared genetic history, antibodies from the same clonotype often bind to the same epitope. This knowledge is used in immune repertoire mining, where known binders are used to search bulk sequencing repertoires to identify new binders. However, current computational methods cannot identify epitope convergence between antibodies from different clonotypes, limiting the sequence diversity of antigen-specific antibodies that can be identified. We describe how the antibody binding site, the paratope, can be used to cluster antibodies with common antigen reactivity from different clonotypes. Our method, paratyping, uses the predicted paratope to identify these novel cross clonotype matches. We experimentally validated our predictions on a pertussis toxoid dataset. Our results show that even the simplest abstraction of the antibody binding site, using only the length of the loops involved and predicted binding residues, is sufficient to group antigen-specific antibodies and provide additional information to conventional clonotype analysis.

Abbreviations: BCR: B-cell receptor; CDR: complementarity-determining region; PTx: pertussis toxoid

Current strategies for detecting functional convergence across B-cell receptor repertoires

Convergence across B-cell receptor (BCR) and antibody repertoires has become instrumental in prioritizing candidates in recent rapid therapeutic antibody discovery campaigns. It has also increased our understanding of the immune system, providing evidence for the preferential selection of BCRs to particular (immunodominant) epitopes post vaccination/infection. These important implications for both drug discovery and immunology mean that it is essential to consider the optimal way to combine experimental and computational technology when probing BCR repertoires for convergence signatures. Here, we discuss the theoretical basis for observing BCR repertoire functional convergence and explore factors of study design that can impact functional signal. We also review the computational arsenal available to detect antibodies with similar functional properties, highlighting opportunities enabled by recent clustering algorithms that exploit structural similarities between BCRs. Finally, we suggest future areas of development that should increase the power of BCR repertoire functional clustering.

Gut Microbiota Composition Modulates the Magnitude and Quality of Germinal Centers during Plasmodium Infections

Gut microbiota composition is associated with human and rodent Plasmodium infections, yet the mechanism by which gut microbiota affects the severity of malaria remains unknown. Humoral immunity is critical in mediating the clearance of Plasmodium blood stage infections, prompting the hypothesis that mice with gut microbiota-dependent decreases in parasite burden exhibit better germinal center (GC) responses. In support of this hypothesis, mice with a low parasite burden exhibit increases in GC B cell numbers and parasite-specific antibody titers, as well as better maintenance of GC structures and a more targeted, qualitatively different antibody response. This enhanced humoral immunity affects memory, as mice with a low parasite burden exhibit robust protection against challenge with a heterologous, lethal Plasmodium species. These results demonstrate that gut microbiota composition influences the biology of spleen GCs as well as the titer and repertoire of parasite-specific antibodies, identifying potential approaches to develop optimal treatments for malaria.

Research has shown that gut microbiota composition influences malaria severity, but the mechanism has remained unclear. Waide et al. show that microbiota composition drives differences in the humoral immune response, including differences in germinal center cell numbers and parasite-specific antibodies, ultimately affecting the memory response to subsequent infection.

immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking

Summary

B- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full-length variable region immune receptor sequences by tuning the following immune receptor features: (i) species and chain type (BCR, TCR, single and paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis, such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis and machine learning methods for motif detection.

Availability and implementation

The package is available via https://github.com/GreiffLab/immuneSIM and on CRAN at https://cran.r-project.org/web/packages/immuneSIM. The documentation is hosted at https://immuneSIM.readthedocs.io.

Contact

sai.reddy@ethz.ch or victor.greiff@medisin.uio.no

Supplementary information

Supplementary data are available at Bioinformatics online.

Genomics-based immuno-oncology: bridging the gap between immunology and tumor biology

The first hypotheses about how the immune system affects cancers were proposed in the early 20th century. These early concepts about cancer immunosurveillance were further developed in the decades that followed, but a detailed understanding of cancer immunity remained elusive. It was only recently, through the advent of high-throughput technologies, that scientists gained the ability to profile tumors with a resolution that allowed for granular assessment of both tumor cells and the tumor microenvironment. The advent of immune checkpoint inhibitors (ICIs), which have proven to be effective cancer therapies in many malignancies, has spawned great interest in developing biomarkers for efficacy, an endeavor that highlighted the value of dissecting tumor immunity using large-scale methods. Response to ICI therapy has been shown to be a highly complex process, where the dynamics of tumor and immune cells is key to success. The need to understand the biologic mechanisms at the tumor-immune interface has given rise to the field of cancer immunogenomics, a discipline that aims to bridge the gap between cancer genomics and classical immunology. We provide a broad overview of this emerging branch of translational science, summarizing common platforms used and recent discoveries in the field, which are having direct clinical implications. Our discussion will be centered around the genetic foundations governing tumor immunity and molecular determinants associated with clinical benefit from ICI therapy. We emphasize the importance of molecular diversity as a driver of anti-tumor immunity and discuss how these factors can be probed using genomic approaches.

Immune Literacy: Reading, Writing, and Editing Adaptive Immunity

Advances in reading, writing, and editing DNA are providing unprecedented insights into the complexity of immunological systems. This combination of systems and synthetic biology methods is enabling the quantitative and precise understanding of molecular recognition in adaptive immunity, thus providing a framework for reprogramming immune responses for translational medicine. In this review, we will highlight state-of-the-art methods such as immune repertoire sequencing, immunoinformatics, and immunogenomic engineering and their application toward adaptive immunity. We showcase novel and interdisciplinary approaches that have the promise of transforming the design and breadth of molecular and cellular immunotherapies.

Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences

Summary

Antibody repertoires reveal insights into the biology of the adaptive immune system and empower diagnostics and therapeutics. There are currently multiple tools available for the annotation of antibody sequences. All downstream analyses such as choosing lead drug candidates depend on the correct annotation of these sequences; however, a thorough comparison of the performance of these tools has not been investigated. Here, we benchmark the performance of commonly used immunoinformatic tools, i.e. IMGT/HighV-QUEST, IgBLAST and MiXCR, in terms of reproducibility of annotation output, accuracy and speed using simulated and experimental high-throughput sequencing datasets.

We analyzed changes in IMGT reference germline database in the last 10 years in order to assess the reproducibility of the annotation output. We found that only 73/183 (40%) V, D and J human genes were shared between the reference germline sets used by the tools. We found that the annotation results differed between tools. In terms of alignment accuracy, MiXCR had the highest average frequency of gene mishits, 0.02 mishit frequency and IgBLAST the lowest, 0.004 mishit frequency. Reproducibility in the output of complementarity determining three regions (CDR3 amino acids) ranged from 4.3% to 77.6% with preprocessed data. In addition, run time of the tools was assessed: MiXCR was the fastest tool for number of sequences processed per unit of time. These results indicate that immunoinformatic analyses greatly depend on the choice of bioinformatics tool. Our results support informed decision-making to immunoinformaticians based on repertoire composition and sequencing platforms.

Availability and implementation

All tools utilized in the paper are free for academic use.

Supplementary information

Supplementary data are available at Bioinformatics online.

GLaMST: grow lineages along minimum spanning tree for b cell receptor sequencing data

Background

B cell affinity maturation enables B cells to generate high-affinity antibodies. This process involves somatic hypermutation of B cell immunoglobulin receptor (BCR) genes and selection by their ability to bind antigens. Lineage trees are used to describe this microevolution of B cell immunoglobulin genes. In a lineage tree, each node is one BCR sequence that mutated from the germinal center and each directed edge represents a single base mutation, insertion or deletion. In BCR sequencing data, the observed data only contains a subset of BCR sequences in this microevolution process. Therefore, reconstructing the lineage tree from experimental data requires algorithms to build the tree based on partially observed tree nodes.

Results

We developed a new algorithm named Grow Lineages along Minimum Spanning Tree (GLaMST), which efficiently reconstruct the lineage tree given observed BCR sequences that correspond to a subset of the tree nodes. Through comparison using simulated and real data, GLaMST outperforms existing algorithms in simulations with high rates of mutation, insertion and deletion, and generates lineage trees with smaller size and closer to ground truth according to tree features that highly correlated with selection pressure.

Conclusions

GLaMST outperforms state-of-art in reconstruction of the BCR lineage tree in both efficiency and accuracy. Integrating it into existing BCR sequencing analysis frameworks can significant improve lineage tree reconstruction aspect of the analysis.

FcRn Overexpression Expands Diversity of the Humoral Immune Response in bFcRn Transgenic Mice

The neonatal Fc receptor (FcRn) plays key roles in IgG and albumin homeostasis, maternal IgG transport, and antigen presentation of IgG-opsonized antigens. Previously, we reported that transgenic (Tg) mice that overexpress bovine FcRn (bFcRn) have augmented T-dependent humoral immune response with increased IgG protection, higher level of antigen-specific antibodies, greater number of antigen-specific B cells, and effective immune response even against weakly immunogenic epitopes. In this study we analyzed the diversity of the humoral immune response of bFcRn Tg mice, using a length distribution analysis (spectratyping) and next generation sequencing (NGS) of the immunoglobulin heavy chain variable regions. Our analysis showed that in response to immunization with ovalbumin or transfected cells that expressed a unique membrane protein, our Tg animals developed a more diverse plasma cell repertoire than controls, which manifested in greater numbers of different clones, and clusters with fewer highly expanded large clones, as identified by the variable region (CDR3) of the immunoglobulin heavy chain. The increased antibody diversity in Tg mice after immunization was observed at both IgM and IgG levels, indicating that the increased humoral immune diversity in Tg mice is due to a higher number of both activated, antigen-specific naïve and isotype switched B cells. We thus demonstrated that the BCR repertoire of the immunized bFcRn Tg animals is more diverse compared to wild type mice, which likely makes these Tg mice a better choice for monoclonal antibody production against challenging antigens, including the extracellular regions of cell membrane proteins.

Polymorphisms in human immunoglobulin heavy chain variable genes and their upstream regions

Germline variations in immunoglobulin genes influence the repertoire of B cell receptors and antibodies, and such polymorphisms may impact disease susceptibility. However, the knowledge of the genomic variation of the immunoglobulin loci is scarce. Here, we report 25 potential novel germline IGHV alleles as inferred from rearranged naïve B cell cDNA repertoires of 98 individuals. Thirteen novel alleles were selected for validation, out of which ten were successfully confirmed by targeted amplification and Sanger sequencing of non-B cell DNA. Moreover, we detected a high degree of variability upstream of the V-REGION in the 5′UTR, L-PART1 and L-PART2 sequences, and found that identical V-REGION alleles can differ in upstream sequences. Thus, we have identified a large genetic variation not only in the V-REGION but also in the upstream sequences of IGHV genes. Our findings provide a new perspective for annotating immunoglobulin repertoire sequencing data.

Data Integration for Immunology

Over the last several years, next-generation sequencing and its recent push toward single-cell resolution have transformed the landscape of immunology research by revealing novel complexities about all components of the immune system. With the vast amounts of diverse data currently being generated, and with the methods of analyzing and combining diverse data improving as well, integrative systems approaches are becoming more powerful. Previous integrative approaches have combined multiple data types and revealed ways that the immune system, both as a whole and as individual parts, is affected by genetics, the microbiome, and other factors. In this review, we explore the data types that are available for studying immunology with an integrative systems approach, as well as the current strategies and challenges for conducting such analyses.

RAbHIT: R Antibody Haplotype Inference Tool

SUMMARY

Antibody haplotype inference (chromosomal phasing) may have clinical implications for the identification of genetic predispositions to diseases. Yet, our knowledge of the genomic loci encoding for the variable regions of the antibody is only partial, mostly due to the challenge of aligning short reads from genome sequencing to these highly repetitive loci. A powerful approach to infer the content of these loci relies on analyzing repertoires of rearranged V(D)J sequences. We present here RAbHIT, an R Haplotype Antibody Inference Tool, that implements a novel algorithm to infer V(D)J haplotypes by adapting a Bayesian framework. RAbHIT offers inference of haplotype and gene deletions. It may be applied to sequences from naïve and non-naïve B-cells, sequenced by different library preparation protocols.

AVAILABILITY AND IMPLEMENTATION

RAbHIT is freely available for academic use from comprehensive R archive network (CRAN) (https://cran.r-project.org/web/packages/rabhit/) under CC BY-SA 4.0 license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

BCR selection and affinity maturation in Peyer's patch germinal centres

The antigen-binding variable regions of the B cell receptor (BCR) and of antibodies are encoded by exons that are assembled in developing B cells by V(D)J recombination1. The BCR repertoires of primary B cells are vast owing to mechanisms that create diversity at the junctions of V(D)J gene segments that contribute to complementarity-determining region 3 (CDR3), the region that binds antigen1. Primary B cells undergo antigen-driven BCR affinity maturation through somatic hypermutation and cellular selection in germinal centres (GCs)2,3. Although most GCs are transient3, those in intestinal Peyer's patches (PPs)-which depend on the gut microbiota-are chronic4, and little is known about their BCR repertoires or patterns of somatic hypermutation. Here, using a high-throughput assay that analyses both V(D)J segment usage and somatic hypermutation profiles, we elucidate physiological BCR repertoires in mouse PP GCs. PP GCs from different mice expand public BCR clonotypes (clonotypes that are shared between many mice) that often have canonical CDR3s in the immunoglobulin heavy chain that, owing to junctional biases during V(D)J recombination, appear much more frequently than predicted in naive B cell repertoires. Some public clonotypes are dependent on the gut microbiota and encode antibodies that are reactive to bacterial glycans, whereas others are independent of gut bacteria. Transfer of faeces from specific-pathogen-free mice to germ-free mice restored germ-dependent clonotypes, directly implicating BCR selection. We identified somatic hypermutations that were recurrently selected in such public clonotypes, indicating that affinity maturation occurs in mouse PP GCs under homeostatic conditions. Thus, persistent gut antigens select recurrent BCR clonotypes to seed chronic PP GC responses.

Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data

Adaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell receptor (BCR) sequence may differ due to the accumulation of somatic hypermutations (SHMs). Clonal relationships are learned from AIRR-seq data by analyzing the BCR sequence, with the most common methods focused on the highly diverse junction region. However, clonally related cells often share SHMs which have been accumulated during affinity maturation. Here, we investigate whether shared SHMs in the V and J segments of the BCR can be leveraged along with the junction sequence to improve the ability to identify clonally related sequences. We develop independent distance functions that capture junction similarity and shared mutations, and combine these in a spectral clustering framework to infer the BCR clonal relationships. Using both simulated and experimental data, we show that this model improves both the sensitivity and specificity for identifying B cell clones. Source code for this method is freely available in the SCOPer (Spectral Clustering for clOne Partitioning) R package (version 0.2 or newer) in the Immcantation framework: www.immcantation.org under the AGPLv3 license.

IgGeneUsage: differential gene usage in immune repertoires

SUMMARY

Decoding the properties of immune repertoires is key to understanding the adaptive immune response to challenges such as viral infection. One important quantitative property is differential usage of Ig genes between biological conditions. Yet, most analyses for differential Ig gene usage are performed qualitatively or with inadequate statistical methods. Here we introduce IgGeneUsage, a computational tool for the analysis of differential Ig gene usage. IgGeneUsage employs Bayesian inference with hierarchical models to analyze complex gene usage data from high-throughput sequencing experiments of immune repertoires. It quantifies differential Ig gene usage probabilistically and avoids some common problems related to the current practice of null-hypothesis significance testing.

AVAILABILITY AND IMPLEMENTATION

IgGeneUsage is an R-package freely available as part of Bioconductor at: https://bioconductor.org/packages/IgGeneUsage/.

CONTACT

simo.kitanovski@uni-due.de.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Extensive dissemination and intraclonal maturation of HIV Env vaccine-induced B cell responses

Well-ordered HIV-1 envelope glycoprotein (Env) trimers are prioritized for clinical evaluation, and there is a need for an improved understanding about how elicited B cell responses evolve following immunization. To accomplish this, we prime-boosted rhesus macaques with clade C NFL trimers and identified 180 unique Ab lineages from ∼1,000 single-sorted Env-specific memory B cells. We traced all lineages in high-throughput heavy chain (HC) repertoire (Rep-seq) data generated from multiple immune compartments and time points and expressed several as monoclonal Abs (mAbs). Our results revealed broad dissemination and high levels of somatic hypermutation (SHM) of most lineages, including tier 2 virus neutralizing lineages, following boosting. SHM was highest in the Ab complementarity determining regions (CDRs) but also surprisingly high in the framework regions (FRs), especially FR3. Our results demonstrate the capacity of the immune system to affinity-mature large numbers of Env-specific B cell lineages simultaneously, supporting the use of regimens consisting of repeated boosts to improve each Ab, even those belonging to less expanded lineages.

VDJbase: an adaptive immune receptor genotype and haplotype database

VDJbase is a publicly available database that offers easy searching of data describing the complete sets of gene sequences (genotypes and haplotypes) inferred from adaptive immune receptor repertoire sequencing datasets. VDJbase is designed to act as a resource that will allow the scientific community to explore the genetic variability of the immunoglobulin (Ig) and T cell receptor (TR) gene loci. It can also assist in the investigation of Ig- and TR-related genetic predispositions to diseases. Our database includes web-based query and online tools to assist in visualization and analysis of the genotype and haplotype data. It enables users to detect those alleles and genes that are significantly over-represented in a particular population, in terms of genotype, haplotype and gene expression. The database website can be freely accessed at https://www.vdjbase.org/, and no login is required. The data and code use creative common licenses and are freely downloadable from https://bitbucket.org/account/user/yaarilab/projects/GPHP.

Repertoire-wide phylogenetic models of B cell molecular evolution reveal evolutionary signatures of aging and vaccination

In order to produce effective antibodies, B cells undergo rapid somatic hypermutation (SHM) and selection for binding affinity to antigen via a process called affinity maturation. The similarities between this process and evolution by natural selection have led many groups to use phylogenetic methods to characterize the development of immunological memory, vaccination, and other processes that depend on affinity maturation. However, these applications are limited by the fact that most phylogenetic models are designed to be applied to individual lineages comprising genetically diverse sequences, while B cell repertoires often consist of hundreds to thousands of separate low-diversity lineages. Further, several features of affinity maturation violate important assumptions in standard phylogenetic models. Here, we introduce a hierarchical phylogenetic framework that integrates information from all lineages in a repertoire to more precisely estimate model parameters while simultaneously incorporating the unique features of SHM. We demonstrate the power of this repertoire-wide approach by characterizing previously undescribed phenomena in affinity maturation. First, we find evidence consistent with age-related changes in SHM hot-spot targeting. Second, we identify a consistent relationship between increased tree length and signs of increased negative selection, apparent in the repertoires of recently vaccinated subjects and those without any known recent infections or vaccinations. This suggests that B cell lineages shift toward negative selection over time as a general feature of affinity maturation. Our study provides a framework for undertaking repertoire-wide phylogenetic testing of SHM hypotheses and provides a means of characterizing dynamics of mutation and selection during affinity maturation.

A spectral clustering-based method for identifying clones from high-throughput B cell repertoire sequencing data

Motivation

B cells derive their antigen-specificity through the expression of Immunoglobulin (Ig) receptors on their surface. These receptors are initially generated stochastically by somatic re-arrangement of the DNA and further diversified following antigen-activation by a process of somatic hypermutation, which introduces mainly point substitutions into the receptor DNA at a high rate. Recent advances in next-generation sequencing have enabled large-scale profiling of the B cell Ig repertoire from blood and tissue samples. A key computational challenge in the analysis of these data is partitioning the sequences to identify descendants of a common B cell (i.e. a clone). Current methods group sequences using a fixed distance threshold, or a likelihood calculation that is computationally-intensive. Here, we propose a new method based on spectral clustering with an adaptive threshold to determine the local sequence neighborhood. Validation using simulated and experimental datasets demonstrates that this method has high sensitivity and specificity compared to a fixed threshold that is optimized for these measures. In addition, this method works on datasets where choosing an optimal fixed threshold is difficult and is more computationally efficient in all cases. The ability to quickly and accurately identify members of a clone from repertoire sequencing data will greatly improve downstream analyses. Clonally-related sequences cannot be treated independently in statistical models, and clonal partitions are used as the basis for the calculation of diversity metrics, lineage reconstruction and selection analysis. Thus, the spectral clustering-based method here represents an important contribution to repertoire analysis.

Availability and implementation

Source code for this method is freely available in the SCOPe (Spectral Clustering for clOne Partitioning) R package in the Immcantation framework: www.immcantation.org under the CC BY-SA 4.0 license.

Supplementary information

Supplementary data are available at Bioinformatics online.

Antibody-based nanotechnology

Antibodies are considered the hallmark of the adaptive immune system in that they mediate various key biological functions, such as direct neutralization and recruitment of effector immune cells to eliminate invading pathogens. Antibodies exhibit several unique properties, including high diversity (enabling binding to a wide range of targets), high specificity and structural integrity. These properties and the understanding that antibodies can be utilized in a wide range of applications have motivated the scientific community to develop new approaches for antibody repertoire analysis and rapid monoclonal antibody discovery. Today, antibodies are key modules in the pharmaceutical and diagnostic industries. By virtue of their high affinity and specificity to their targets and the availability of technologies to engineer different antibodies to a wide range of targets, antibodies have become the most promising natural biological molecules in a range of biotechnological applications, such as: highly specific and sensitive nanobiosensors for the diagnostics of different biomarkers; nanoparticle-based targeted drug delivery systems to certain cells or tissues; and nanomachines, which are nanoscale mechanical devices that enable energy conversion into precise mechanical motions in response to specific molecular inputs. In this review, we start by describing the unique properties of antibodies, how antibody diversity is generated, and the available technologies for antibody repertoire analysis and antibody discovery. Thereafter, we provide an overview of some antibody-based nanotechnologies and discuss novel and promising approaches for the application of antibodies in the nanotechnology field. Overall, we aim to bridge the knowledge gap between the nanotechnology and antibody engineering disciplines by demonstrating how technological advances in the antibody field can be leveraged to develop and/or enhance new technological approaches in the nanotechnology field.

Application of immune repertoire sequencing in cancer immunotherapy

With the prominent breakthrough in the field of tumor immunology, diverse cancer immunotherapies have attracted great attention in the last decade. The immune checkpoint inhibitors, adoptive cell therapies, and therapeutic cancer vaccines have already achieved impressive clinical success. However, the fact that only a small subset of patients with specific tumor types can benefit from these treatments limits the application of cancer immunotherapy. To seek out the molecular mechanisms behind this challenge and to select cancer precision medicine for different individuals, researchers apply the immune repertoire sequencing (IRS) to evaluate genetic responses of each patient to current immunotherapies. This review summarizes the technical advances and recent applications of IRS in cancer immunotherapy, indicates the limitations of this technique, and predicts future perspectives both in basic studies and clinical trials.

Functional Enrichment and Analysis of Antigen-Specific Memory B Cell Antibody Repertoires in PBMCs

Phenotypic screening of antigen-specific antibodies in human blood is a common diagnostic test for infectious agents and a correlate of protection after vaccination. In addition to long-lived antibody secreting plasma cells residing in the bone marrow, memory B cells are a latent source of antigen-experienced, long-term immunity that can be found at low frequencies in circulating peripheral blood mononuclear cells (PBMCs). Assessing the genotype, clonal frequency, quality, and function of antibodies resulting from an individual's persistent memory B cell repertoire can help inform the success or failure of immune protection. Using in vitro polyclonal stimulation, we functionally expand the memory repertoire from PBMCs and clonally map monoclonal antibodies from this population. We show that combining deep sequencing of stimulated memory B cell repertoires with retrieving single antigen-specific cells is a promising approach in evaluating the latent, functional B cell memory in PBMCs.

Survival analysis of DNA mutation motifs with penalized proportional hazards

Antibodies, an essential part of our immune system, develop through an intricate process to bind a wide array of pathogens. This process involves randomly mutating DNA sequences encoding these antibodies to find variants with improved binding, though mutations are not distributed uniformly across sequence sites. Immunologists observe this nonuniformity to be consistent with "mutation motifs", which are short DNA subsequences that affect how likely a given site is to experience a mutation. Quantifying the effect of motifs on mutation rates is challenging: a large number of possible motifs makes this statistical problem high dimensional, while the unobserved history of the mutation process leads to a nontrivial missing data problem. We introduce an ℓ 1-penalized proportional hazards model to infer mutation motifs and their effects. In order to estimate model parameters, our method uses a Monte Carlo EM algorithm to marginalize over the unknown ordering of mutations. We show that our method performs better on simulated data compared to current methods and leads to more parsimonious models. The application of proportional hazards to mutation processes is, to our knowledge, novel and formalizes the current methods in a statistical framework that can be easily extended to analyze the effect of other biological features on mutation rates.

Single cell immune profiling in transplantation research

Recently developed single-cell profiling technologies hold promise to provide new insights including analysis of population heterogeneity and linkage of antigen receptors with gene expression. These technologies produce complex data sets that require knowledge of bioinformatics for appropriate analysis. In this minireview, we discuss several single-cell immune profiling technologies for gene and protein expression, including cytometry by time-of-flight, RNA sequencing, and antigen receptor sequencing, as well as key considerations for analysis that apply to each. Because of the critical importance of data analysis for high parameter single cell analysis, we discuss essential factors in analysis of these data, including quality control, quantification, examples of methods for high dimensional analysis, immune repertoire analysis, and preparation of analysis pipelines. We provide examples of, and suggestions for, application of these innovative methods to transplantation research.

The Pipeline Repertoire for Ig-Seq Analysis

With the advent of high-throughput sequencing of immunoglobulin genes (Ig-Seq), the understanding of antibody repertoires and their dynamics among individuals and populations has become an exciting area of research. There is an increasing number of computational tools that aid in every step of the immune repertoire characterization. However, since not all tools function identically, every pipeline has its unique rationale and capabilities, creating a rich blend of useful features that may appear intimidating for newcomer laboratories with the desire to plunge into immune repertoire analysis to expand and improve their research; hence, all pipeline strengths and differences may not seem evident. In this review we provide a practical and organized list of the current set of computational tools, focusing on their most attractive features and differences in order to carry out the characterization of antibody repertoires so that the reader better decides a strategic approach for the experimental design, and computational pathways for the analyses of immune repertoires.

Characterizing pre-transplant and post-transplant kidney rejection risk by B cell immune repertoire sequencing

Studying immune repertoire in the context of organ transplant provides important information on how adaptive immunity may contribute and modulate graft rejection. Here we characterize the peripheral blood immune repertoire of individuals before and after kidney transplant using B cell receptor sequencing in a longitudinal clinical study. Individuals who develop rejection after transplantation have a more diverse immune repertoire before transplant, suggesting a predisposition for post-transplant rejection risk. Additionally, over 2 years of follow-up, patients who develop rejection demonstrate a specific set of expanded clones that persist after the rejection. While there is an overall reduction of peripheral B cell diversity, likely due to increased general immunosuppression exposure in this cohort, the detection of specific IGHV gene usage across all rejecting patients supports that a common pool of immunogenic antigens may drive post-transplant rejection. Our findings may have clinical implications for the prediction and clinical management of kidney transplant rejection.

iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories

Next-generation sequencing allows the characterization of the adaptive immune receptor repertoire (AIRR) in exquisite detail. These large-scale AIRR-seq data sets have rapidly become critical to vaccine development, understanding the immune response in autoimmune and infectious disease, and monitoring novel therapeutics against cancer. However, at present there is no easy way to compare these AIRR-seq data sets across studies and institutions. The ability to combine and compare information for different disease conditions will greatly enhance the value of AIRR-seq data for improving biomedical research and patient care. The iReceptor Data Integration Platform (gateway.ireceptor.org) provides one implementation of the AIRR Data Commons envisioned by the AIRR Community (airr-community.org), an initiative that is developing protocols to facilitate sharing and comparing AIRR-seq data. The iReceptor Scientific Gateway links distributed (federated) AIRR-seq repositories, allowing sequence searches or metadata queries across multiple studies at multiple institutions, returning sets of sequences fulfilling specific criteria. We present a review of the development of iReceptor, and how it fits in with the general trend toward sharing genomic and health data, and the development of standards for describing and reporting AIRR-seq data. Researchers interested in integrating their repositories of AIRR-seq data into the iReceptor Platform are invited to contact support@ireceptor.org.

Large-scale network analysis reveals the sequence space architecture of antibody repertoires

The architecture of mouse and human antibody repertoires is defined by the sequence similarity networks of the clones that compose them. The major principles that define the architecture of antibody repertoires have remained largely unknown. Here, we establish a high-performance computing platform to construct large-scale networks from comprehensive human and murine antibody repertoire sequencing datasets (>100,000 unique sequences). Leveraging a network-based statistical framework, we identify three fundamental principles of antibody repertoire architecture: reproducibility, robustness and redundancy. Antibody repertoire networks are highly reproducible across individuals despite high antibody sequence dissimilarity. The architecture of antibody repertoires is robust to the removal of up to 50-90% of randomly selected clones, but fragile to the removal of public clones shared among individuals. Finally, repertoire architecture is intrinsically redundant. Our analysis provides guidelines for the large-scale network analysis of immune repertoires and may be used in the future to define disease-associated and synthetic repertoires.

Inferred Allelic Variants of Immunoglobulin Receptor Genes: A System for Their Evaluation, Documentation, and Naming

Immunoglobulins or antibodies are the main effector molecules of the B-cell lineage and are encoded by hundreds of variable (V), diversity (D), and joining (J) germline genes, which recombine to generate enormous IG diversity. Recently, high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) of recombined V-(D)-J genes has offered unprecedented insights into the dynamics of IG repertoires in health and disease. Faithful biological interpretation of AIRR-seq studies depends upon the annotation of raw AIRR-seq data, using reference germline gene databases to identify the germline genes within each rearrangement. Existing reference databases are incomplete, as shown by recent AIRR-seq studies that have inferred the existence of many previously unreported polymorphisms. Completing the documentation of genetic variation in germline gene databases is therefore of crucial importance. Lymphocyte receptor genes and alleles are currently assigned by the Immunoglobulins, T cell Receptors and Major Histocompatibility Nomenclature Subcommittee of the International Union of Immunological Societies (IUIS) and managed in IMGT®, the international ImMunoGeneTics information system® (IMGT). In 2017, the IMGT Group reached agreement with a group of AIRR-seq researchers on the principles of a streamlined process for identifying and naming inferred allelic sequences, for their incorporation into IMGT®. These researchers represented the AIRR Community, a network of over 300 researchers whose objective is to promote all aspects of immunoglobulin and T-cell receptor repertoire studies, including the standardization of experimental and computational aspects of AIRR-seq data generation and analysis. The Inferred Allele Review Committee (IARC) was established by the AIRR Community to devise policies, criteria, and procedures to perform this function. Formalized evaluations of novel inferred sequences have now begun and submissions are invited via a new dedicated portal (https://ogrdb.airr-community.org). Here, we summarize recommendations developed by the IARC-focusing, to begin with, on human IGHV genes-with the goal of facilitating the acceptance of inferred allelic variants of germline IGHV genes. We believe that this initiative will improve the quality of AIRR-seq studies by facilitating the description of human IG germline gene variation, and that in time, it will expand to the documentation of TR and IG genes in many vertebrate species.

Oligoclonal immunoglobulin repertoire in biliary remnants of biliary atresia

Biliary atresia (BA) is a neonatal cholestatic liver disease that is the leading cause of pediatric liver transplantation, however, the mechanism of disease remains unknown. There are two major forms of BA: isolated BA (iBA) comprises the majority of cases and is thought to result from an aberrant immune response to an environmental trigger, whereas syndromic BA (BASM) has associated malformations and is thought to arise from a congenital insult. To determine whether B cells in BA biliary remnants are antigen driven, we examined the immunoglobulin (Ig) repertoire of diseased tissue from each BA group. Deep sequencing of the Ig chain DNA was performed on iBA and BASM biliary remnants and lymph nodes obtained from the Childhood Liver Disease Research Network (ChiLDReN) repository. Statistical analysis of the Ig repertoire provided measures of Ig clonality and the Ig phenotype. Our data demonstrate that B cells infiltrate diseased iBA and BASM biliary remnant tissue. The Ig repertoires of iBA and BASM disease groups were oligoclonal supporting a role for an antigen-driven immune response in both sub-types. These findings shift the current understanding of BA and suggest a role for antigen stimulation in early iBA and BASM disease pathogenesis.

Landscape of B cell immunity and related immune evasion in human cancers

Tumor-infiltrating B cells are an important component in the microenvironment but have unclear anti-tumor effects. We enhanced our previous computational algorithm TRUST to extract the B cell immunoglobulin hypervariable regions from bulk tumor RNA-sequencing data. TRUST assembled more than 30 million complementarity-determining region 3 sequences of the B cell heavy chain (IgH) from The Cancer Genome Atlas. Widespread B cell clonal expansions and immunoglobulin subclass switch events were observed in diverse human cancers. Prevalent somatic copy number alterations in the MICA and MICB genes related to antibody-dependent cell-mediated cytotoxicity were identified in tumors with elevated B cell activity. The IgG3-1 subclass switch interacts with B cell-receptor affinity maturation and defects in the antibody-dependent cell-mediated cytotoxicity pathway. Comprehensive pancancer analyses of tumor-infiltrating B cell-receptor repertoires identified novel tumor immune evasion mechanisms through genetic alterations. The IgH sequences identified here are potentially useful resources for future development of immunotherapies.